Inspecting Method and Inspecting Apparatus For Substrate Surface

ABSTRACT

An inspecting method and apparatus for inspecting a substrate surface includes illuminating a light to the substrate surface having a film, detection of a scattered light or reflected light from a plurality of positions of the substrate surface to obtain a plurality of electrical signals, comparison of the plurality of electrical signals and a database which indicates a relationship between the electrical signals and surface roughness, and calculation of a surface roughness value based on the result of comparison.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. application Ser. No.13/404,749, filed Feb. 24, 2012, which is a continuation of U.S.application Ser. No. 12/470,505, filed Feb. 22, 2009, now U.S. Pat. No.8,144,337, the contents of which are incorporated herein by reference.

BACKGROUND OF THE INVENTION

The present invention relates to an inspecting method and an inspectingapparatus for inspecting the surface roughness existing on the surfaceof a substrate such as a semiconductor substrate or a hard disksubstrate.

In a manufacturing line for the semiconductor substrate or thin filmsubstrate, the inspection for defect or foreign matter existing on thesurface of the semiconductor substrate or thin film substrate is made tomaintain and improve the yields of products. For example, in a samplesuch as a semiconductor substrate before forming a circuit pattern, itis required to detect a microscopic defect or foreign matter(hereinafter called a defect) of 0.05 μm or less on the surface ormicroroughness (haze) on the surface. Also, to detect such defect, theconventional inspecting apparatus applies a condensed laser beam to thesurface of the sample and condenses and detects a scattered light fromthe defect. Also, in a sample such as a semiconductor substrate afterforming the circuit pattern, the sample surface is illuminated by alaser beam, a scattered light occurring on the sample surface iscondensed, a diffracted light from a periodical pattern is shielded by aspatial filter, a scattered light from a non-periodic pattern and thedefect is detected, and the non-periodic pattern is deleted by diecomparison to recognize the defect.

A semiconductor inspection among various kinds of substrate inspectionwill be described below by way of example. On a wafer after passingthrough various kinds of semiconductor manufacturing process for asilicon wafer or film formation, there are various defects, whichdecrease the yields of the semiconductor products. As a degree ofintegration of the semiconductor product is increased, it is requiredthat the surface inspection of the substrate has the higher sensitivityand the defects are classified and detected. There are various kinds ofdefects such as foreign matter, scratch and COP (crystalline defect),and further there is recently a demand for detecting the microroughnesson the surface of the substrate.

These prior arts were described in patent document 1 (JP-A-2003-130808),non-patent document 1 (APPLIED OPTICS 1995 Vol. 34, No. 1 pp. 201-208),non-patent document 2 (P. A. Bobbert and J. Vlieger (Leiden Univ.):Light Scattering), non-patent document 3 (S. O. Rice, Comm. Pure andAppl. Math 4, 351 (1951)), non-patent document 4 (J. M. Elson; Lightscattering from surfaces with a single dielectric overlayer; J. Opt.Soc. Am. 66, 682-694 (1976)), non-patent document 5 (J. M. Elson:Infrared light scattering from surface covered with multiple dielectricoverlayers; Appl. Opt. 16, 2872-2881 (1977)), and non-patent document 6(J. M. Elson: Multilayer-coated optics: guided-wave coupling andscattering by means of interface random roughness; J. Opt. Soc. Am. A12,729-742 (1995)).

SUMMARY OF THE INVENTION

As the degree of integration of the semiconductor product is increased,it is required that the surface inspection of the substrate has thehigher sensitivity, and the defects are classified and detected, wherebythere is a demand for detecting the microroughness on the surface of thesubstrate as its object.

However, in the optical inspecting apparatuses as disclosed in the abovedocuments, the inspection for the microroughness or film thicknessvariation existing on the substrate surface could not be made at thehigh sensitivity and high speed.

The invention provides an inspecting method and an inspecting apparatusfor detecting the microroughness on the substrate surface at the highsensitivity and high speed.

Also, the invention provides an inspecting method and an inspectingapparatus capable of making the inspection for the microroughness andthe inspection for defects on the substrate surface at the same time.

The typical inventions as disclosed in the present application will bebriefly outlined as follows.

(1) An inspecting method for inspecting a substrate surface,characterized by including a first step of applying a light to thesubstrate surface, a second step of detecting a scattered light orreflected light from the substrate surface due to the applied light at aplurality of positions to obtain a plurality of electrical signals, athird step of extracting a signal in a mutually different frequency bandfrom each of the plurality of electrical signals, and a fourth step ofcalculating a value regarding the surface roughness of the substratesurface to through an arithmetical operation process of a plurality ofextracted signals in the frequency bands.

(2) The inspecting method according to (1), characterized in that thethird step includes extracting the signal in the frequency bandpreprogrammed for each of the plurality of electrical signals.

(3) An inspecting apparatus for inspecting a substrate surface,characterized by comprising an illuminating optical system for applyinga light to the substrate surface, a plurality of detecting opticalsystems for detecting a scattered light or reflected light from thesubstrate surface due to the applied light at a plurality of positionsto obtain a plurality of electrical signals, and a processing sectionfor extracting a signal in a mutually different frequency band from eachof the plurality of electrical signals, and calculating a valueregarding the surface roughness of the substrate surface through anarithmetical operation process of a plurality of extracted signals inthe frequency bands.

(4) The inspecting apparatus according to (3), characterized in that theplurality of detecting optical systems are arranged at mutuallydifferent elevation angles.

(5) The inspecting apparatus according to (3) or (4), characterized inthat at least one detecting optical system of the plurality of detectingoptical systems has a beam splitter for splitting the optical path ofthe scattered light or reflected light and a plurality of sensorsarranged on a plurality of optical paths split by the beam splitter, andan analyzer is disposed on the optical path of one sensor of theplurality of sensors.

(6) The inspecting method according to (1) or (2), characterized in thatthe fourth step includes calculating a plurality of values regarding thesurface roughness.

(7) The inspecting apparatus according to any of (3) to (5),characterized in that a plurality of pieces of information on thesurface roughness are calculated.

(8) An inspecting method for inspecting a substrate surface,characterized by including a first step of applying a light to thesubstrate surface, a second step of detecting a scattered light orreflected light from the substrate surface due to the applied light at aplurality of positions to obtain a plurality of electrical signals, anda third step of comparing the plurality of signals and the data havingthe correspondences between the surface roughness on the substratehaving different surface roughness and the plurality of signals andestimating the surface roughness.

(9) An inspecting apparatus for inspecting a substrate surface,characterized by comprising an illuminating optical system for applyinga light to the substrate surface, a plurality of detecting opticalsystems for detecting a scattered light or reflected light from thesubstrate surface due to the applied light at a plurality of positionsto obtain a plurality of electrical signals, and a processing sectionfor calculating a value regarding the surface roughness of the substratesurface by making a comparison process between the plurality of signalsand the data having the correspondences between the surface roughness onthe substrate having different surface roughness and the plurality ofsignals.

These and other objects, features and advantages of the invention willbe apparent from the following more particular description of preferredembodiments of the invention, as illustrated in the accompanyingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a view showing a first embodiment of an inspecting apparatusaccording to the present invention.

FIG. 2A is a first view showing a relatively scanning method between asubstrate and an illumination.

FIG. 2B is a second view showing a relatively scanning method betweenthe substrate and the illumination.

FIG. 2C is a third view showing a relatively scanning method between thesubstrate and the illumination.

FIG. 3A is a view showing a detection signal waveform.

FIG. 3B is a view showing a defective signal waveform at high frequency.

FIG. 3C is a view showing a wafer surface state signal waveform at lowfrequency.

FIG. 4 is a view showing one example of a detecting element having fourdetecting optical systems.

FIG. 5A is an upper view showing one example of the numerical aperturein the detecting element having a plurality of detection systems.

FIG. 5B is a side view showing one example of the numerical aperture inthe detecting element having the plurality of detection systems.

FIG. 6A is a view showing a frequency band distribution detectable inapplying the light vertically to the inspection object substrate.

FIG. 6B is a view showing the frequency band distribution detectable inapplying the light obliquely to the inspection object substrate.

FIG. 7A is a view showing the frequency band distribution of surfaceroughness detectable by each detector in the four detection systemshaving different detection angles.

FIG. 7B is a view showing the relationship between the light intensityof is substrate surface roughness and the frequency band detectable byeach detector in a case where there are four detection systems havingdifferent detection angles.

FIG. 8A is a view showing the frequency band distribution of surfaceroughness detectable by each detector in five or more detection systemshaving different detection angles.

FIG. 8B is a view showing the relationship between the light intensityof substrate surface roughness and the frequency band detectable by eachdetector in a case where there are five or more detection systems havingdifferent detection angles.

FIG. 9( a 1) is a first view showing one example of a surface state map.

FIG. 9( a 2) is a view showing the cross-sectional waveform for thesurface state detection value or RMS value in a state of FIG. 9( a 1).

FIG. 9( a 3) is a view showing a frequency distribution of the surfacestate detection value or RMS value on the entire surface of thesubstrate in the state of FIG. 9( a 1).

FIG. 9( b 1) is a second view showing one example of the surface statemap.

FIG. 9( b 2) is a view showing the cross-sectional waveform for thesurface state detection value or RMS value in the state of FIG. 9( b 1).

FIG. 9( b 3) is a view showing the frequency distribution of the surfacestate detection value or RMS value on the entire surface of thesubstrate in the state of FIG. 9( b 1).

FIG. 9( c 1) is a third view showing one example of the surface statemap.

FIG. 9( c 2) is a view showing the cross-sectional waveform for thesurface state detection value or RMS value in the state of FIG. 9( c 1).

FIG. 9( c 3) is a view showing the frequency distribution of the surfacestate detection value or RMS value on the entire surface of thesubstrate in the state of FIG. 9( c 1).

FIG. 9( d 1) is a fourth view showing one example of the surface statemap.

FIG. 9( d 2) is a view showing the cross-sectional waveform for thesurface state detection value or RMS value in the state of FIG. 9( d 1).

FIG. 9( d 3) is a view showing the frequency distribution of the surfacestate detection value or RMS value on the entire surface of thesubstrate in the state of FIG. 9( d 1).

FIG. 10 is a view showing an embodiment of a detection system in whichthe detecting optical path is separated.

FIG. 11 is a view for explaining the configuration of a signalprocessing section in an inspecting apparatus according to theinvention.

FIG. 12 is a view showing the correlation between surface roughness,RMS(Rq) and apparatus output.

FIG. 13A is a first view showing an example in which the substratesurface is spatially divided into areas.

FIG. 13B is a second view showing an example in which the substratesurface is spatially divided into areas.

FIG. 14 is a view showing one example of trend data in a wafer surfacestate.

FIG. 15 is a coordinate system in a BRDF calculation expression.

FIG. 16 is an example of measurement result outputs.

FIG. 17 is a view showing the measurement results and the database.

FIG. 18 is a view showing how the signal value for each detector isdisplayed in the three dimensional space.

FIG. 19A is a first view showing the relationship in the shape betweenthe top surface layer and its lower layer in a multilayer substrate.

FIG. 19B is a second view showing the relationship in the shape betweenthe top surface layer and its lower layer in the multilayer substrate.

FIG. 20 is a view showing the comparison between the measured signal andthe database.

FIG. 21 is a view showing the relationship between input and output inan algorithm for estimating the surface state.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The embodiments of the present invention will be described below byexemplifying an inspecting apparatus that detects a defect on thesurface of a wafer without pattern formed (bare wafer, or wafer in whichbare wafer is subjected to a film formation process, a washing process,or a polishing process).

The inspecting apparatus according to the invention appropriatelycomprises an illuminating optical system 1001 for applying light to asubstrate of inspection object, a stage scanning section 1003 forinspecting all or part of the substrate, a detecting optical system 1002for detecting the scattered light or reflected light, a signalprocessing section 1004 for determining the defect or haze, and a dataprocessing control section 50 for making the post-processing for thedetected defect or haze. Each configuration will be specificallydescribed below.

The illuminating optical system 1001 as shown in FIG. 1 has an obliquelyilluminating optical system for applying an illuminating light 1 a fromthe oblique direction to an inspection object substrate 2 and avertically illuminating optical system for applying an illuminatinglight 1 b from the vertical direction, which can be switched by moving amovable mirror 13, and appropriately comprises a light source 10, alight quantity adjustment mechanism 11, the light flux shape adjustmentmechanisms 12, 15 a and 15 b, the mirrors 13, 14 and 18, the polarizers16 a and 16 b, the phase shifters 17 a and 17 b, and the lenses 19 a and19 b. The explanation is given below, taking the use of obliqueillumination as an example.

A light emitted from the light source 10 such as a laser is adjustedinto a desired light quantity and a beam shape through the lightquantity adjustment mechanism 11 and the light flux adjustment mechanism12, diverted in the optical path by the mirror 13 (or alternatively abeam splitter), and adjusted again in the beam shape by the light fluxadjustment mechanism 15 a. The light is made the specific illuminationof linearly polarized light by the polarizer 16 a, adjusted into adesired polarized state (P polarized light, S polarized light or Cpolarized light) by the phase shifter 17 a, and applied via the mirror18 and the projection lens 19 a to the inspection object substrate 2. Ina projected state of illumination on the inspection object substrate 2,an illumination spot 9 is linearly narrowed in an elliptical shape or inone direction, as shown in FIG. 2.

The light source 10 uses a laser of visible light wavelength band or UVwavelength band (wavelength band of 400 nm or less). Each of the lightflux adjustment mechanisms 12 and 15 a may be a beam expander orcylindrical lens (or alternatively an anamorphic prism), and shapes theillumination form on the substrate in combination with the projectionlens 19 a in the illuminating optical system 1001. The light quantityadjustment mechanism 11 is used to adjust the light quantity to desiredquantity, depending on the film materials or film thickness of thesubstrate, using an attenuator or neutral density filter, and Thepolarizer 16 a also functions as a wavelength selector, and is used toreduce the light other than the main wavelength component included inthe illuminating light. The phase shifter 17 a of a polarizationadjustment section is comprised of a half-wave plate or a quarterwavelength plate, and is used to adjust polarization of illumination. Inthis embodiment, an optical path switching section is provided for theillumination to allow a selection between two optical paths of obliqueillumination and almost vertical illumination to the substrate, but itis not required that two angles of incidence for illumination areprovided, and one or three or more angles may be provided. In additionto the method for making a switching between oblique illumination andvertical illumination, using the movable mirror 13 as the optical pathswitching section, as shown in FIG. 1, both the oblique illumination andthe vertical illumination can be effected at the same time, using a beamsplitter. Though the foreign matter is typically more sensitive in theoblique illumination, a concave defect such as scratch or COP may beoften more sensitive in the vertical illumination, whereby it ispossible to use properly or jointly the illuminating angles depending onthe defect species to be detected.

The stage scanning section 1003 is a mechanism for applying theillumination spot shaped by the illuminating optical system 1001 to allor part of the substrate surface, and comprises a substrate supportingmechanism 4 for supporting the substrate, a Z stage 5 for adjusting theheight of the substrate, a θ stage 6 for rotating the substrate, and anR stage 7 for translating the substrate in the fixed direction. Herein,a scanning method for the inspection object substrate 2 will bedescribed below using FIG. 2. If the θ stage 6 is rotated relative tothe illumination spot 9 firstly applied near the edge of the inspectionobject substrate 2, the light is successively applied near the edge ofthe substrate along the circumferential direction. At the same time, ifthe R stage 7 is translated in one direction, the illumination spot issuccessively moved on the substrate surface in the circumferentialdirection and the radial direction, radially scanning the entire surfaceor any area of the substrate, as shown in FIG. 2A. Herein, if theillumination spot 9 is in the elliptical or linear form, it is possibleto perform the scanning at high speed. The scanning of the illuminationspot is not limited to the above method, but the specific radialposition may be scanned once or multiple times, and then the R stage 7may be moved, as shown in FIG. 2B. The focusing of the inspection objectsubstrate 2 and the illumination spot 9 is adjusted to reach a desiredheight by the Z stage 5.

Though the stage scanning section 1003 has been described above byexemplifying the R-θ stage, it is necessary to scan all or part of thesubstrate surface by the illumination spot 9 relatively moving on thesubstrate, in which an X-Y stage or a mechanism for moving theillumination side may be used, as shown in FIG. 2C.

The detecting optical system 1002 as shown in FIG. 1 is composed of twodetecting optical systems, and appropriately comprises the lenses 105and 115 for condensing the scattered light or reflected light that isradiated at a certain azimuth or elevation angle from the inspectionobject substrate 2 due to the light applied by the illuminating opticalsystem 1001 for a predetermined numerical aperture (NA), the analyzers104 and 114 for extracting any polarized light component only from thecondensed scattered light or reflected light, the band pass filters 103and 113 for reducing a stray light, the neutral density filters 102 and112 for adjusting the light quantity, and the sensors 101 and 111.Herein, an instance of using two detecting optical systems havingdifferent elevation angles has been described above, but alternatively,four detection systems may be provided at different elevation angles, asshown in FIG. 4. In the invention, it is important that the detectingoptical systems may be provided at a plurality of azimuth or elevationangles, as will be described later.

Herein, the sensors 101 and 111 are elements for converting the incidentlight into a voltage or current for output, and may be a photomultiplieror CCD sensor. If the photomultiplier is employed as the sensor, themultiplication factor (gain) of the signal is adjusted in accordancewith a dynamic range of the signal processing system 1004 at the latterstage of the sensor or a scattered light quantity of the inspectionobject substrate 2. Though a detection example of the light bycombination of lens and sensor has been described above in the detectingoptical system 1002 as shown in FIG. 1, it is necessary that the lightradiated at a plurality of azimuth or elevation angles may be detectedby the sensors independently, and a combination of a mirror or adiffractive light element may be employed.

Next, the signal processing system 1004 for making the defectdetermination and surface roughness determination will be describedbelow. The signal processing system 1004 appropriately comprises thepreamplifiers 151 and 161 for amplifying a detection signal from eachsensor 101, 111 in the plurality of detecting optical systems, and asignal processing circuit section 30 for performing the requiredamplification, a noise process and an analog to digital conversionprocess. Particularly if the photomultiplier is employed as the sensor101, 111, the preamplifiers 151 and 161 are used because the output is aweak current. The outputs from the preamplifiers 151 and 161 areprocessed independently or by adding the signals in the signalprocessing section 30.

Herein, FIG. 3 shows one example of the signal (current or voltage)detected by the sensor, in which the horizontal axis represents the time(or position because the radial scanning is made) and the vertical axisis indicated with the detected light intensity or signal value. Adetection signal of the scattered light quantity caused by a defect onthe substrate surface and a detection signal caused by a surface stateof the substrate are detected at the same time, as shown in FIG. 3A. Byextracting a specific frequency component only in the signal processingcircuit section 30, it is possible to separate a signal of highfrequency as a defective signal (FIG. 3B) and a signal of low frequencyas a wafer surface state signal (FIG. 3C), and thereby employ the signalin the high frequency band for defect detection and the signal in thelow frequency band for surface state detection. Also, the signalprocessing section 30 has a function of adding the signals in theplurality of detecting optical systems. The addition of signals in theplurality of detection systems may be made in a digital processingsection, not an analog processing section. Besides, in the digitalprocessing section of the signal processing section 30, a thresholdvalue is set to the signal in the high frequency band, and the signalbeyond the threshold value is detected as the defect, whereby thedetection signal value and existence position (position in the R-θcoordinates) at that time are stored in a storage section 60 at thelatter stage. Also, for the signal in the low frequency band, the signalvalue is detected as the surface state detection value, and thedetection signal value and existence position are stored in the storagesection 60 at the latter stage. For the signal added in the analogprocessing section, the same process is conducted to detect the defectand the surface state. In the section for adding the signals from thedifferent detection systems, the gain and offset are adjusted dependingon an individual difference of the sensor or analog board beforeaddition. Also, any sensor of the plurality of sensors may be increasedin the gain for defect detection (e.g., application voltage is increasedin the photomultiplier) to make the inspection, in which case the signalprocessing board for the surface state measurement is adjusted so thatthe gain of each sensor may be apparently equal, that is, the gain ofthe circuit board for the sensor with increased gain may be decreasedand conversely the gain of the circuit board may be increased if thegain of the sensor is low. Though two signals are added in thisembodiment, the number of signals is not necessarily limited to two, andany number of signals may be added, or the signals may be added afteradjustment of signal in each detection system at any ratio in making theaddition.

Next, a software processing control section 50 will be described below.In the software processing control section 50, an additional functionalpost-processing is performed for the detected defect signal or surfacestate signal. For example, the defect size calculation, the defectclassification, and the conversion of the surface state signal into theRMS value may be performed. If the data of the film materials or filmthickness is provided beforehand, the size calculation at highprecision, the classification and the conversion into the RMS value canbe made by using the data. Though not shown, the control of theilluminating optical system 1001, the stage scanning section 1003, thesensor gain and the circuit board is also performed in the softwareprocessing control section 50. The software processing control section50 is configured by a personal computer, and connected to the storagesection 60, input means 70 and display means 80. Also, it is connectedto communication means for connecting to the host system or relevantsystem and has a function of controlling the overall system.

Referring now to FIGS. 5 to 8, the relationship between the detectionsystem and the surface roughness of the inspection object substrate willbe described below.

FIG. 5 shows the numerical aperture (NA) of the detection sectioncomposed of the four detection systems arranged at the first elevationangle and mutually different azimuth angles and the six detectionsystems arranged at the second elevation angle and mutually differentazimuth angles as one example of the detection section, wherein FIG. 5Ais its upper view and FIG. 5B is its side view. The followingexplanation is given taking this detection section as an example, asneeded.

FIG. 6 shows the correspondences between the detection system and thesurface roughness of the inspection object substrate in the frequencyspace. Assuming that the wavelength of illumination is λ, the incidentangle is θi, the detection angle of the detection system is θs and theazimuth angle is φs, the relationship between the frequency of surfaceroughness and the position of the detection system is represented basedon the relationship of light diffraction in the following expression.

$\begin{matrix}{f_{x} = \frac{{\sin \; \theta_{s}\cos \; \varphi_{s}} - {\sin \; \theta_{i}}}{\lambda}} & \left\lbrack {{Numerical}\mspace{14mu} {expression}\mspace{14mu} 1} \right\rbrack \\{f_{y} = \frac{\sin \; \theta_{s}\sin \; \varphi_{s}}{\lambda}} & \left\lbrack {{Numerical}\mspace{14mu} {expression}\mspace{14mu} 2} \right\rbrack\end{matrix}$

FIG. 6A shows a frequency band distribution detectable in applying thelight vertically (θi=0) to the inspection object substrate and FIG. 6Bshows a frequency band distribution detectable in applying lightobliquely (θi=80) to the inspection object substrate, taking the case ofFIG. 5 previously described as an example. As will be clear from theabove expression and FIG. 6, the specific frequency band is onlydetectable among the frequency components of the substrate surfaceroughness, in which the detectable frequency band is wider as theincident angle of illumination is larger. Also, if the plurality ofdetection systems are provided, the plurality of specific frequencybands only can be detected independently.

FIG. 7 shows the relationship between the detection system and thesurface roughness of the inspection object substrate in the frequencyspace from another viewpoint of FIG. 6. FIG. 7A shows the frequencycomponents of surface roughness detectable in each detection system,using an instance where there are four detection system having differentdetection angles as previously described and shown in FIG. 4. If theilluminating light 1 is incident at the incident angle θi of about 80degrees upon the inspection object substrate 2, the detector closer tothe reflected light of illumination detects the low frequency componentof substrate surface roughness and the other detectors detect the higherfrequency components in order clockwise in FIG. 7A. FIG. 7B shows therelationship between the light intensity (detection signal) of substratesurface roughness and the frequency band detectable in the detectionsystem.

Herein, since the light quantity detectable in the detection system isdetected by condensing (i.e., integrating) the scattered lightcorresponding to the specific frequency band, the square of the RMSvalue of substrate surface roughness is the integral value of powerspectrum in the specific frequency band, and the energy of signalwaveform is conserved before and after the Fourier transformation(Parseval's theorem), it follows that the square value of the RMS valueand the detected light quantity compute the scalar quantity of the samequality by combining the frequency bands for the detection system and incomputing the RMS value. That is, it is indicated that the RMS value ofsubstrate surface roughness can be calculated from the detected lightquantity corrected by the light quantity of illumination, thereflectance of the substrate or the gain of the detection system. Fromthe above, the RMS value of substrate surface roughness corresponding tothe specific frequency band only can be detected by independentlycalculating the surface state based on the scattered light quantitydetected in each of the detection systems. Also, the RMS valuecorresponding to the overall frequency band detectable in the detectionsystems can be detected by adding the scattered light quantity in eachof the detection systems.

FIGS. 8A and 8B, like FIG. 7, show the relationship between thedetection system and the surface roughness of the inspection objectsubstrate in the frequency space, in which more detection systems aredisposed than in FIG. 7. With more detectors, more accurate frequencyinformation can be acquired.

Herein, a display example of the detected surface state detection valueor RMS value for each frequency band is shown for the entire surface ofthe substrate based on the coordinate information in FIG. 9. FIG. 9( a1) shows a surface state map, FIG. 9( a 2) shows a cross-sectionalwaveform of the surface state detection value or RMS value, and FIG. 9(a 3) shows a frequency distribution of the surface state detection valueor RMS value on the entire surface of the substrate. FIGS. 9( b 1) to9(b 3), FIGS. 9( c 1) to 9(c 3) and FIGS. 9( d 1) to 9(d 3) show thesurface state map, cross-sectional waveform and frequency distributionof the wafers having different surface states in the same way.

Referring to FIG. 10, an embodiment of the detection system for makingthe defect inspection and the surface state inspection at the same timewill be described below. For the defect inspection, it is required toremove the scattering on the wafer surface as much as possible toincrease the S/N, and it is effective to reduce and detect the scatteredlight from the wafer surface using an analyzer. On the other hand, ininspecting the wafer surface state, it causes negative effect that thelight is removed by the analyzer. Thus, a beam splitter 106 is mountedto split the light into two optical paths for defect detection andsurface state detection, and the analyzer 104 is disposed on only oneoptical path, as shown in FIG. 10, whereby both functions can beachieved at the same time. In this case, a signal processing circuit fordefect detection may have a high pass filter alone, and a signalprocessing circuit for surface state detection may have a low passfilter alone.

Referring to FIG. 12, the relationship between the surface roughness ofwafer and the RMS will be described below. Though the measurement of thewafer surface is made in three dimensions, the explanation is given herein two dimensions for simplicity. First of all, the surface roughness ofwafer is represented in the following expression, using the position xand the height z.

z=g(x)  [Numerical expression 3]

At this time, the constant term of the function g(x) is adjusted so thatthe average height of wafer may be z=0. Making the Fouriertransformation of the function g(x), the function is transformed intothe frequency space. The function F(g(x)) after the Fouriertransformation at this time is generally called a PSD function.

Herein, the square value of the RMS(Rq) value is the integration of theaverage value (i.e., z=0) of the function g(x). Also, owing to theParseval's theorem, the integral value of g(x) and the integral value ofthe PSD function after the Fourier transformation are equal, whereby theRMS value can be computed if the PSD function is known.

On the other hand, for the light scattering on the wafer in the surfaceshape with z=g(x), if the scattered light is detected in the pluralityof detecting optical systems disposed at different positions, and thesignal to be extracted in the frequency band preprogrammed in accordancewith the position of the detector is extracted and measured from theobtained detection signal, as already described, the output very similarto the PSD function can be detected. This output is the value of the PSDfunction multiplied by the optical constant of wafer and the conditions(wavelength, polarization) of the optical system in the form offunction, as described in non-patent document 1 (APPLIED OPTICS 1995Vol. 34, No. 1 pp. 201-208). The conditions of the optical system, whichare known information for the apparatus creator, can be easily obtained.Also, the optical constant of wafer is usable by acquiring beforehandthe data for each wafer to be inspected. To acquire beforehand the data,there are a method for making the measurement in creating the inspectionconditions, a method for inputting the data measured in anotherapparatus, a method for making the measurement for each inspection, anda method for prestoring the film materials and the reflectance data inthe storage section 60.

As described above, the signal obtained by the light scatteringmeasurement is firstly converted into the PSD function, and the PSDfunction is further integrated, whereby the RMS (Rq) value can becalculated.

Next, a space dividing example of the inspection object surface requiredin evaluating the inspection result of the surface state will bedescribed below. In the defect inspection, the general condition ofwafer may be grasped based on the statistic such as the number ofdefects, in addition to the position, size and kind of defect, and inthe surface state inspection of wafer, if there is the similarstatistic, it is easier to grasp the general condition. Thus, if theupper limit value of the surface state inspection signal or the RMS ispreset by dividing the space in the form of FIG. 13A or 13B, it ispossible to monitor the space dividing point or its number in the areaexceeding the upper limit value on the entire surface of wafer.

FIG. 14 shows one example of trend data in the surface state of wafer.On display means 80, the average RMS value on the entire surface ofwafer, the average output value of each sensor, or the number of areasexceeding the upper limit value on the entire surface of wafer aspreviously described are displayed successively for each wafer, wherebythe state of wafer can be is grasped in time series.

In connection with FIG. 4, the scattering of light owing to particles onthe substrate can be represented in the following expression [non-patentdocument 2 (P. A. Bobbert and J. Vlieger (Leiden Univ.): LightScattering)].

$\begin{matrix}{{{B\; R\; D\; F} = {\frac{16\pi^{4}}{\lambda^{4}}\left( \frac{{\text{?}n_{sph}^{2}} - 1}{{n_{sph}^{2}\text{?}} + 2} \right)^{2}\frac{NF}{A}\frac{a^{6}}{\cos \; \theta_{s}\cos \; \theta_{i}}{{\text{?} \cdot \hat{e}}}^{2}}}{\text{?}\text{?}\text{indicates text missing or illegible when filed}}} & \left\lbrack {{Numerical}\mspace{14mu} {expression}\mspace{14mu} 4} \right\rbrack\end{matrix}$

Herein, the BRDF, which is called a bidirectional reflectancedistribution function, is a function inherent to the reflection spot,representing how much light quantity is reflected in each direction whenthe light is incident on a certain spot x on the reflecting (scattering)surface from a certain direction. In a rough representation, thereflectance is generalized.

Wherein π is the ratio of the circumference of a circle to its diameter,λ, is the illumination wavelength (μm), n_(sph) is the refractive indexof particle, N/A is the density (number/μm) of particles within theillumination area, and F is a structure factor depending on thepositional relationship of the noticed scatterer with another scattererexisting nearby. If the scatterers exist randomly, F=1. Also, a is theradius (μm) of particle, θs and θi are the detection angle and theincident angle (degree), and ̂e is a unit vector of incident light inthe electric field direction. The coordinate system is shown in FIG. 15,which is an explanation view of variables for use in the numericalexpression of the BRDF (bidirectional reflectance distribution function)as previously described. Q^(part) is the parameter of polarization, andhas the following four combinations of incident light and detectedpolarized light. Q_(SP) means the S polarization incidence and Ppolarization detection.

Q _(ss)=[1+βr _(s) ¹²(θ_(s))][1+αr _(s) ¹²(θ_(i))]cos φ_(s)

Q _(sp)=−[1+βr _(p) ¹²(θ_(s))][1+αr _(s) ¹²(θ_(i))]cos θ_(s) sin φ_(s)

Q _(ps)=−[1+βr _(s) ¹²(θ_(s))][1−αr _(p) ¹²(θ_(i))]cos θ_(i) sin φ_(s)

Q _(pp)=[1+βr _(p) ¹²(θ_(p))][1+αr _(p) ¹²(θ_(i))]sin θ_(i) sinφ_(s)−[1−βr _(p) ¹²(θ_(s))][1−αr _(p) ¹²(θ_(i))]cos θ_(s) cosθ_(i) sinθ_(s)  [Numerical expression 5]

Wherein α=exp(ika·cos θi) is the phase difference corresponding to theoptical path length difference between the incident light and thereflected light, and β=exp(ika·cos θs) is the phase differencecorresponding to the optical path length difference between thescattered light and the reflected light without being scattered. Also,r_(p) ¹²(θ) and r_(s) ¹²(θ) are the Fresnel's formulas for reflection,represented in the following expressions. The superscript 12 denotes thereflection factor on the medium 1 and the medium 2, and the subscripts pand s mean the P polarization and the S polarization. The circularlypolarized light and the elliptically polarized light are considered inthe S polarization component and the P polarization component.

$\begin{matrix}{{{r_{p}^{12}(\theta)} = \frac{{\left( {n_{2}/n_{1}} \right)^{2}\cos \; \theta} - \left\lbrack {\left( {n_{2}/n_{1}} \right)^{2} - {\sin^{2}\theta}} \right\rbrack^{1/2}}{{\left( {n_{2}/n_{1}} \right)^{2}\cos \; \theta} + \left\lbrack {\left( {n_{2}/n_{1}} \right)^{2} - {\sin^{2}\theta}} \right\rbrack^{1/2}}}{{r_{s}^{12}(\theta)} = \frac{{\cos \; \theta} - \left\lbrack {\left( {n_{2}/n_{1}} \right)^{2} - {\sin^{2}\theta}} \right\rbrack^{1/2}}{{\cos \; \theta} + \left\lbrack {\left( {n_{2}/n_{1}} \right)^{2} - {\sin^{2}\theta}} \right\rbrack^{1/2}}}} & \left\lbrack {{Numerical}\mspace{14mu} {expression}\mspace{14mu} 6} \right\rbrack\end{matrix}$

Also, the light scattering due to the surface roughness of the substratecan be represented in the following expression [non-patent document 3(S. O. Rice, Comm. Pure and Appl. Math 4, 351 (1951))].

$\begin{matrix}{{B\; R\; D\; F} = {\frac{16\pi^{2}}{\lambda^{4}}\cos \; \theta_{s}\cos \; \theta_{i}{S(f)} \times {{Q^{topo} \cdot \hat{e}}}^{2}}} & \left\lbrack {{Numerical}\mspace{14mu} {expression}\mspace{14mu} 7} \right\rbrack\end{matrix}$

The BRDF is a bidirectional reflectance distribution function asdescribed in the section of the light scattering owing to the particles.S(f) is called the PSD function, representing the power spectrum inconsidering that the substrate surface is composed of a combination ofsurface structures at various frequencies. Q^(topo) is the parameter ofpolarization and has the following four combinations with the incidenceand detection polarization. Q_(SP) means the S polarization incidenceand the P polarization detection. In the film of which the surface isoptically opaque, Q_(topo) is as follows.

Q _(ss) =Q _(s0) cos φ_(s)

Q _(sp) =−Q _(s0)(n _(mat) ²−sin θ_(s))^(1/2) sin φ_(s)

Q _(ps) =Q _(p0)(n ² _(mat)−sin θ_(i))^(1/2) sin φ_(s)

Q _(pp) =−Q _(p0) [n ² _(mat) sin θ_(i) sin φ_(s)−(n ² _(mat)−sinθ_(i))^(1/2)(n _(mat)−sin θ_(s))^(1/2) cos φ_(s)]  [Numerical expression8]

Wherein n_(mat) is the refractive index of the substrate.

$\begin{matrix}{\mspace{79mu} {{Q_{s\; 0} = \frac{\text{?} - 1}{\begin{matrix}\left\lbrack {{\cos \; \theta_{i}} + \left( {n_{mat}^{2} - {\sin \; \theta_{i}}} \right)^{1/2}} \right\rbrack \\\left\lbrack {{\cos \; \theta_{s}} + \left( {n_{mat}^{2} - {\sin \; \theta_{s}}} \right)^{1/2}} \right\rbrack\end{matrix}}}\mspace{79mu} {Q_{p\; 0} = \frac{\text{?} - 1}{\begin{matrix}\left\lbrack {{n_{mat}^{2}\cos \; \theta_{i}} + \left( {n_{mat}^{2} - {\sin \; \theta_{i}}} \right)^{1/2}} \right\rbrack \\\left\lbrack {{n_{mat}^{2}\cos \; \theta_{s}} + \left( {n_{mat}^{2} - {\sin \; \theta_{s}}} \right)^{1/2}} \right\rbrack\end{matrix}}}{\text{?}\text{indicates text missing or illegible when filed}}}} & \left\lbrack {{Numerical}\mspace{14mu} {expression}\mspace{14mu} 9} \right\rbrack\end{matrix}$

The light quantity to be detected may change depending on not only thesubstrate surface state S(t) but also the polarized state ofillumination or polarization detection, and the conditions of theoptical system such as the incident angle and azimuth angle ofillumination and the elevation angle and azimuth angle of detection, asdescribed above. Therefore, if the surface state of the substrate isevaluated by the light scattering under the same optical conditions, therelative evaluation is allowed, but if comparison is made under thedifferent optical conditions, it is required to make the appropriatecomputation based on the above numerical expressions.

Besides, if a plurality of detectors are used and the scattered light isdetected by changing the sensitivity or gain of each detector, it isrequired to make the appropriate correction for them.

Since the detecting optical system has the numerical aperture (NA), theis light scattering owing to the particles and the light scatteringowing to the surface roughness are detected by condensing the light forNA in the detecting optical system (the BRDF function is integrated forNA).

FIG. 16 shows the measurement results on the entire surface of theinspection object substrate in one example of the measurement resultoutputs. A detector integrated measurement map indicating the data addedin analog or digital, the histogram information of the detectorintegrated measurement map and a detection map of each detector areillustrated. The BRDF value, the RMS value, and the film thickness valuemay be selectively outputted. Also, the statistic such as average valueor maximum value may be displayed from each measurement result.

FIG. 17 shows the signal value of each detector for the inspectionobject substrate and a detection signal database of the substrate inwhich the surface roughness is known. For the substrate in which thesurface roughness is known, the signal value of each detector isobtained beforehand by measurement or simulation and stored in thedatabase. By comparison with the signal value of each detector for theinspection object substrate, the surface roughness of the inspectionobject substrate can be estimated.

Now, it is assumed that there are n detectors, and the signal value ofeach detector for the inspection object substrate is (s1, s2, s3, sn).On the other hand, it is assumed that the signal value of each detectorfor the substrate in which the surface roughness is known is (d11, d12,d13, d1 n), (d21, d22, d23, d2 n), . . . , and (dm1, dm2, dm3, dmn), thedetection data of surface roughness can be represented as amultidimensional vector in which the signal value of each detector isthe component. The degree of surface roughness of the inspection objectsubstrate can be estimated by evaluating the degree of coincidencebetween the vector in the database and the vector of the inspectionobject substrate. If each surface roughness is associated with the RMSvalue in the database, the RMS value of the inspection object substratecan be estimated immediately.

FIG. 18 is a view plotting the detection signal value for two kinds ofsubstrates having different surface states in the three dimensionalspace, supposing a case where there are three detectors for simplicity.As an evaluation index of the degree of coincidence of vectors, theEuclid distance between vectors, the weighted Euclid distance, or theangle between vectors may be employed. Also, the obtained detectionsignal is not directly made the component of vector, but oncelogarithmically converted, and the distance may be evaluated using thevector after logarithmic conversion.

A method with the Euclid distance between vectors as the evaluationindex of the degree of coincidence of vectors will be described below asan example. It is supposed that there are the surface roughness 1 andthe surface roughness 2 as the database, and the signal value of eachdetector for each roughness is (d11,d12,d13) and (d21,d22,d23). Now, itis supposed that when a sample in which the state of surface roughnessis unknown (the surface roughness m is assumed here) is inspected, thesignal of each detector is (dm1,dm2,dm3). Since the Euclid distancebetween vectors is the square root of the square sum of differencesbetween components of the vector, the Euclid distance between thesurface roughness m and the surface roughness 1 and the Euclid distancebetween the surface roughness m and the surface roughness 2 arerepresented in the following expressions.

$\begin{matrix}{{{{Distance}\mspace{14mu} {between}\mspace{14mu} {surface}\mspace{14mu} {roughness}\mspace{14mu} m\mspace{14mu} {and}\mspace{14mu} {surface}\mspace{14mu} {roughness}\mspace{14mu} 1} = \sqrt{\sum\limits_{k = 1}^{3}\left( {{d\; 1k} - {dmk}} \right)^{2}}}} & \left\lbrack {{Numerical}\mspace{14mu} {expression}\mspace{14mu} 10} \right\rbrack \\{{{Distance}\mspace{14mu} {between}\mspace{14mu} {surface}\mspace{14mu} {roughness}\mspace{14mu} m\mspace{14mu} {and}\mspace{14mu} {surface}\mspace{14mu} {roughness}\mspace{14mu} 2} = \sqrt{\sum\limits_{k = 1}^{3}\left( {{d\; 2k} - {dmk}} \right)^{2}}} & \left\lbrack {{Numerical}\mspace{14mu} {expression}\mspace{14mu} 11} \right\rbrack\end{matrix}$

The smaller one of the distances obtained in this way is employed asapproximate data of the surface roughness m.

Also, as another example, in the case of the weighted Euclid distance,the following expression is used in calculating the Euclid distance.

$\begin{matrix}{{{Distance}\mspace{14mu} {between}\mspace{14mu} {surface}\mspace{14mu} {roughness}\mspace{14mu} m\mspace{14mu} {and}\mspace{14mu} {surface}\mspace{14mu} {roughness}\mspace{14mu} 1} = \sqrt{\sum\limits_{k = 1}^{3}{w_{k}\left( {{d\; 1k} - {dmk}} \right)}^{2}}} & \left\lbrack {{Numerical}\mspace{14mu} {expression}\mspace{14mu} 12} \right\rbrack \\{{{Distance}\mspace{14mu} {between}\mspace{14mu} {surface}\mspace{14mu} {roughness}\mspace{14mu} m\mspace{14mu} {and}\mspace{14mu} {surface}\mspace{14mu} {roughness}\mspace{14mu} 2} = \sqrt{\sum\limits_{k = 1}^{3}{w_{k}\left( {{d\; 2k} - {dmk}} \right)}^{2}}} & \left\lbrack {{Numerical}\mspace{14mu} {expression}\mspace{14mu} 13} \right\rbrack\end{matrix}$

Wherein w_(k) is the weighting coefficient vector. If the value of eachcomponent of w_(k) is 1, the weighted Euclid distance is equal to theEuclid distance.

If the detection signal of the surface roughness is once logarithmicallyconverted and the distance is calculated, the distance between thesurface roughness m and the surface roughness 1 is represented in thefollowing expression.

$\begin{matrix}{{{Distance}\mspace{14mu} {between}\mspace{14mu} {surface}\mspace{14mu} {roughness}\mspace{14mu} m\mspace{14mu} {and}\mspace{14mu} {surface}\mspace{14mu} {roughness}\mspace{14mu} 1} = \sqrt{\sum\limits_{k = 1}^{3}{w_{k}\left( {{\log \left( {d\; 1k} \right)} - {\log ({dmk})}} \right)}^{2}}} & \left\lbrack {{Numerical}\mspace{14mu} {expression}\mspace{14mu} 14} \right\rbrack\end{matrix}$

As another example of the evaluation index of the degree of coincidenceof vectors, the angle between two vectors may be used. From the formulaof the inner product of any two vectors OA and OB, the followingexpression holds for the angle θ between two vectors.

OA·OB=|OA∥OB|cos θ

θ=arccos(OA·OB/|OA∥OB|)

From the above, the angle between the surface roughness m and thesurface roughness 1 is represented in the specific expression asfollows.

θ=arcos[(d11·dm1+d12·dm2+d13·dm3)/{√(d11² +d12² +d13²)·√(dm1² +dm ²+dm3²)}]  [Numerical expression 16]

In this case, the angle between the vector of each surface roughnessexisting in the database and the vector m in which the surface roughnessof inspection object is unknown is obtained, and the vector of thesmallest value in the database is employed as approximate data of thesurface roughness m.

Though the evaluation method for the degree of coincidence of vectorshas been described above by way of example, a basic concept of theinvention is to estimate the surface roughness based on the detectionsignals of the plurality of detectors, namely, the spatial distributionof the light scattering intensity, and the invention is not limited tothe above embodiments, but needless to say, may be changed in variousways without departing from the spirit or scope of the invention.

Though the invention has been described above in the instance in whichthe surface roughness only is changed, the light scattering changesdepending on not only the state of surface roughness, but also adifference of film materials on the top surface or a difference of filmthickness if the film is transparent to the illumination wavelength.Thus, a database in which each of the surface roughness, film thicknessand film materials is changed is created, and comparison is made withthe signal value of each detector for the inspection object substrate,whereby the surface roughness, film thickness and film materials can beestimated at the same time.

The creation of the database is made by creating the reference samplesand actually collecting the measurement data or making the simulation.

The case of actually collecting the measurement data will be describedbelow. A plurality of samples having the different states of surfaceroughness are prepared, as shown in FIG. 19A. The light scattering witheach sample is measured beforehand, and the detection signal in eachdetector is prepared. For the samples having different states of surfaceroughness, the standard samples commercially available on the market maybe used, and a method for changing the etching conditions such as blendof chemicals or etching time in etching the surface with the chemicalsolution, or a method for changing the polishing conditions such aspolishing pressure or polishing time in polishing the surface may beused. In the film formation wafer, the film formation conditions such astemperature or pressure in forming the film may be changed.

A method of computation will be described below using FIGS. 18B and 18C.FIG. 18B is a view showing a method for measuring the prepared samplehaving different surface roughness with an AFM (atomic forcemicroscope), computing the light scattering with the crenelationcondition of the surface as input data, and storing it in the database.In the computation, instead of measuring the surface state of the samplewith the AFM, a model of any surface state may be created and the lightscattering may be computed to create the database. The computationmethods for the light scattering in this case may include an FDTDmethod, and a DDA method, besides the BRDF method as previouslydescribed. FIG. 18C is a view showing the BRDF method. With the BRDFmethod, a PSD function for the surface roughness is used as an inputvariable for the light scattering computation, and a plurality ofarbitrary PSD function models are created to compute the lightscattering, thereby creating the database. In the BRDF method, Q^(topo)is calculated depending on the film materials or film thickness, evenfor the sample having different film materials or film thickness,whereby the light scattering can be computed [non-patent document 4 (J.M. Elson: Light scattering from surfaces with a single dielectricoverlayer; J. Opt. Soc. Am. 66, 682-694 (1976)), and non-patent document5 (J. M. Elson: Infrared light scattering from surface covered withmultiple dielectric overlayers; Appl. Opt. 16, 2872-2881 (1977)), 6].

$\begin{matrix}{{B\; R\; D\; F} = {\frac{16\pi^{2}}{\lambda^{4}}\cos \; \theta_{s}\cos \; \theta_{i}{S(f)} \times {{Q^{topo} \cdot \hat{e}}}^{2}}} & \left\lbrack {{Numerical}\mspace{14mu} {expression}\mspace{14mu} 17} \right\rbrack\end{matrix}$

FIG. 19 is a view showing the cases in which the film is transparent tothe illumination wavelength. If a very thin film or film with excellentwettability is on the top surface, the film conforming to the surfaceshape of under-layer is formed (FIG. 19A). In this case, the surfaceroughness of the top surface and the surface roughness of theunder-layer are almost identical. On the other hand, if the filmthickness is large, or the film with less wettability is on the toplayer, the surface roughness is uncorrelated with the surface state ofthe substratum, whereby the surface roughness of the substratum isdifferent between the top surface and the under-layer, as shown in FIG.19B. According to [non-patent documents 4, 5 and 6], the value ofQ^(topo) is changed because of these differences, and in computing thelight scattering of the film having transparent surface with thesubstrate by simulation, it is required to consider the film thicknessor film materials.

FIG. 20 is a view showing a scheme for improving the computationefficiency in making the comparison with the database. If theinformation on the film materials or film thickness can be acquiredbefore inspection, the search space can be reduced, and the evaluationfor the degree of coincidence of vectors can be made faster. The filmmaterials or film thickness may be inputted by the user who measures thesubstrate, or an ellipsometer may be mounted on a measurement samplealignment portion of the inspecting apparatus, for example, to measurethe (optical constant of) film specifies or film thickness in parallelwith the alignment. In this case, the computation efficiency can beimproved without having any influence on the total inspection time ofthe substrate. If the approximate value of the film thickness is known,even though the accurate value is unknown, the search range can bereduced, whereby the computation efficiency is improved by inputting theapproximate value. Also, using these information, there is less risk ofestimating the different substrate indicating the similar scatteringintensity distribution, even if the film materials or film thickness andthe surface roughness are different, whereby the higher estimationprecision can be expected.

A summary of the above described contents is represented in FIG. 21. Aprocess 40 involves a computation algorithm for estimating the filmmaterials, film thickness and surface state. The input values includethe signal value of each detector, film materials, film thickness, anddata on the surface roughness of the under-layer in the transparentfilm, in which the film materials, film thickness, and data on thesurface roughness of the under-layer are used, only if available. Theprocess 40 includes comparing the inputted signal value of each detectorwith the database, and estimating the surface roughness, film materialsand film thickness. In the comparison with the database, if the distancebetween vectors is larger (in a sparse state in which there is no datacloser to light scattering of the inspection object substrate in thedatabase), the surface state of inspection object substrate may beestimated by a method of linear interpolation, using some vectors in theneighborhood.

Though the present invention has been specifically described above basedon the embodiment of the invention achieved by the present inventor, theinvention is not limited to the above embodiment, but needless to say,may be changed in various ways without departing from the spirit orscope of the invention. Also, though the inspecting apparatus fordetecting the surface defect of the wafer has been exemplified in theabove embodiment, the application object of the invention is not limitedto this, and the techniques of the invention can be applied to thesurface inspection of various kinds of substrate, such as the disksurface inspection of a hard disk or the like, a glass substrateinspection of liquid crystal or the like, photo mask surface inspection,in addition to the semiconductor substrate inspection.

With the invention, it is possible to provide an inspecting method andan inspecting apparatus for detecting the microroughness of thesubstrate surface at high sensitivity and high speed.

The invention may be embodied in other specific forms without departingfrom the spirit or essential characteristics thereof. The presentembodiment is therefore to be considered in all respects as illustrativeand not restrictive, the scope of the invention being indicated by theappended claims rather than by the foregoing description and all changeswhich come within the meaning and range of equivalency of the claims aretherefore intended to be embraced therein.

1. An inspecting method for inspecting a substrate surface,characterized by including: a first step of illuminating a light to thesubstrate surface having a film; a second step of detecting a scatteredlight or reflected light from a plurality of positions of the substratesurface and obtaining a plurality of electrical signals; a third step ofcomparing the plurality of electrical signals and a database whichindicates a relationship between the electrical signals and surfaceroughness; and a fourth step of calculating a surface roughness valuebased on the result of comparing of the third step.
 2. The inspectingmethod according to claim 1, wherein the database is obtained beforehandby measurement or simulation.
 3. The inspecting method according toclaim 1, characterized in that the third step includes comparing theplurality of electrical signals and a database which indicates arelationship between the electrical signals and film thickness;characterized in that the fourth step includes calculating a filmthickness based on the result of comparing of the third step.
 4. Theinspecting method according to claim 1, characterized in that the thirdstep includes comparing the plurality of electrical signals and adatabase which indicates a relationship between the electrical signalsand film materials; characterized in that the fourth step includescalculating a film material based on the result of comparing of thethird step.
 5. The inspecting method according to claim 1, wherein thedatabase indicates a relationship between the electrical signals of arespective detector and surface roughness.
 6. An inspecting apparatusfor inspecting a substrate surface, characterized by including: anilluminator which illuminates a light to the substrate surface having afilm; at least one detector which a scattered light or reflected lightfrom a plurality of positions of the substrate surface and obtaining aplurality of electrical signals; a comparator which compares theplurality of electrical signals and a database which indicates arelationship between the electrical signals and surface roughness; and acalculator which calculates a surface roughness value based on theresult of comparing of the comparator.
 7. The inspecting apparatusaccording to claim 6, wherein the database is obtained beforehand bymeasurement or simulation.
 8. The inspecting apparatus according toclaim 1, characterized in that the comparator includes a comparingdevice which compares the plurality of electrical signals and a databasewhich indicates a relationship between the electrical signals and filmthickness; characterized in that the calculator calculates a filmthickness based on the result of comparing of the comparing device. 9.The inspecting apparatus according to claim 6, characterized in that thecomparator includes a comparing device which compares the plurality ofelectrical signals and a database which indicates a relationship betweenthe electrical signals and film materials; characterized in that thecalculator calculates a film material based on the result of comparingof the comparing device.
 10. The inspecting apparatus according to claim6, wherein the database indicates a relationship between the electricalsignals of a respective detector and surface roughness.